Literaturnachweis - Detailanzeige
| Autor/in | Roberts, James S. |
|---|---|
| Titel | Modified Likelihood-Based Item Fit Statistics for the Generalized Graded Unfolding Model |
| Quelle | In: Applied Psychological Measurement, 32 (2008) 5, S.407-423 (17 Seiten)
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0146-6216 |
| DOI | 10.1177/0146621607301278 |
| Schlagwörter | Item Response Theory; Goodness of Fit; Test Items; Models; Simulation; Psychometrics; Scores; Error Patterns; Probability; Evaluation Methods |
| Abstract | Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a unidimensional IRT model for unfolding polytomous responses. It yields single-peaked, non-monotonic item characteristic curves that predict a higher item score to the extent that an individual is located close to an item on the underlying latent continuum. A simulation was performed to examine the characteristics of these new item fit indices under the GGUM, as well as a traditional likelihood ratio x[superscript 2] test (G[superscript 2]). All variants of S-X[superscript 2] exhibited reasonable Type I error rates, but that for G[superscript 2] was more erratic. The new indices exhibited variable power to detect misfit. Two new item fit tests are recommended for use based on simulation results. (Contains 1 figure and 4 tables.) (As Provided). |
| Anmerkungen | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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